Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Chapter A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living / / Bernadette Dorizzi
| Chapter A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living / / Bernadette Dorizzi |
| Autore | Dorizzi Bernadette |
| Pubbl/distr/stampa | [Place of publication not identified] : , : IntechOpen, , 2012 |
| Descrizione fisica | 1 online resource |
| Disciplina | 511.313 |
| Soggetto topico | Fuzzy logic |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910774653703321 |
Dorizzi Bernadette
|
||
| [Place of publication not identified] : , : IntechOpen, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Intelligence and Mathematics for Tackling Complex Problems [[electronic resource] /] / edited by László T Kóczy, Jesús Medina-Moreno, Eloísa Ramírez-Poussa, Alexander Šostak
| Computational Intelligence and Mathematics for Tackling Complex Problems [[electronic resource] /] / edited by László T Kóczy, Jesús Medina-Moreno, Eloísa Ramírez-Poussa, Alexander Šostak |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XVII, 200 p. 43 illus., 29 illus. in color.) |
| Disciplina | 511.313 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Engineering—Data processing Computer mathematics Artificial intelligence Computational Intelligence Data Engineering Computational Science and Engineering Artificial Intelligence |
| ISBN | 3-030-16024-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Speakers. -Chapter 1. Hierarchical fuzzy decision support methodology for dangerous goods packaging design -- Chapter 2. Towards Automatic Web Identification of Solutions in Patient Innovation -- Chapter 3. The Discrete Bacterial Memetic Evolutionary Algorithm for solving the one-commodity Pickup-and-Delivery Traveling Salesman Problem -- Chapter 4. Roughness and Fuzziness, etc. |
| Record Nr. | UNINA-9910484599903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Intelligence and Soft Computing : Recent Applications / / Kóczy T. László, István A. Harmati, editors
| Computational Intelligence and Soft Computing : Recent Applications / / Kóczy T. László, István A. Harmati, editors |
| Pubbl/distr/stampa | Base Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2023 |
| Descrizione fisica | 1 online resource (458 pages) |
| Disciplina | 511.313 |
| Soggetto topico | Fuzzy systems |
| ISBN | 3-0365-6156-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Computational Intelligence and Soft Computing |
| Record Nr. | UNINA-9910719774003321 |
| Base Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Contemporary fuzzy logic : a perspective of fuzzy logic with Scilab / / Stefania Tomasiello, Witold Pedrycz and Vincenzo Loia
| Contemporary fuzzy logic : a perspective of fuzzy logic with Scilab / / Stefania Tomasiello, Witold Pedrycz and Vincenzo Loia |
| Autore | Tomasiello Stefania |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] |
| Descrizione fisica | 1 online resource (141 pages) |
| Disciplina | 511.313 |
| Collana | Big and Integrated Artificial Intelligence |
| Soggetto topico |
Fuzzy logic
Artificial intelligence Computational intelligence |
| ISBN | 3-030-98974-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910568242803321 |
|
Tomasiello Stefania
|
||
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Explainable Uncertain Rule-Based Fuzzy Systems
| Explainable Uncertain Rule-Based Fuzzy Systems |
| Autore | Mendel Jerry M |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (598 pages) |
| Disciplina | 511.313 |
| ISBN | 3-031-35378-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- References -- Contents -- About the Author -- 1: Introduction -- 1.1 What This Book Is About -- 1.1.1 Rules -- 1.1.2 Partitions and Sets -- 1.1.2.1 Crisp Partitions -- 1.1.2.2 First-Order Uncertainty Partitions -- 1.1.2.3 Second-Order Uncertainty Partitions: Uniformly Weighted -- 1.1.2.4 Second-Order Uncertainty Partitions: Nonuniformly Weighted -- 1.1.2.5 Footprint of Uncertainty (FOU) -- 1.1.2.6 Comments -- 1.2 The Structure of a Rule-Based Fuzzy System -- 1.3 A New Direction for Fuzzy Systems -- 1.4 Fundamental Design Requirement -- 1.5 Advisable Design Approaches -- 1.6 Understanding the Potential for Improved Performance -- 1.7 Explainable Fuzzy Systems -- 1.8 An Impressionistic Brief History of Type-1 Fuzzy Sets and Fuzzy Logic -- 1.9 Literature on Type-2 Fuzzy Sets and Fuzzy Systems -- 1.9.1 Early Literature: 1975-1992 -- 1.9.2 Publications that Heavily Influenced the First Edition of This Book -- 1.9.3 Most Cited Articles -- 1.10 Coverage -- 1.11 Applicability Outside of Rule-Based Fuzzy Systems -- 1.12 Computation -- References -- 2: Type-1 Fuzzy Sets and Fuzzy Logic -- 2.1 Crisp Sets -- 2.2 Type-1 Fuzzy Sets and Associated Concepts -- 2.2.1 Lotfi A. Zadeh -- 2.2.2 Type-1 Fuzzy Set Defined -- 2.2.3 Type-1 Fuzzy Numbers -- 2.2.4 Linguistic Variables -- 2.2.5 Returning to Linguistic Labels from Numerical Values of MFs -- 2.3 Set Theoretic Operations for Crisp Sets -- 2.4 Set Theoretic Operations for Type-1 Fuzzy Sets -- 2.5 Crisp Relations and Compositions on the Same Product Space -- 2.6 Fuzzy Relations and Compositions on the Same Product Space -- 2.7 Crisp Relations and Compositions on Different Product Spaces -- 2.8 Fuzzy Relations and Compositions on Different Product Spaces -- 2.9 Hedges -- 2.10 Extension Principle -- 2.11 α-Cuts -- 2.12 Representing Type-1 Fuzzy Sets Using α-Cuts.
2.13 Functions of Type-1 Fuzzy Sets Computed by Using α-Cuts -- 2.14 Multivariable MFs and Cartesian Products -- 2.15 Crisp Logic -- 2.16 From Crisp Logic to Fuzzy Logic -- 2.17 Mamdani (Engineering) Implications -- 2.18 Remarks -- 1.1 Laws That Are Satisfied -- 1.2 Laws That Are Not Satisfied -- Appendix 2: Cardinality and Similarity -- 2.1 Cardinality of Type-1 Fuzzy Sets -- 2.2 Similarity of Type-1 Fuzzy Sets -- References -- 3: Type-1 Fuzzy Systems -- 3.1 Type-1 Fuzzy Systems -- 3.2 Rules -- 3.3 Fuzzifier -- 3.4 Fuzzy Inference Engine -- 3.4.1 General Results -- 3.4.2 Fuzzification and Its Effects on Inference -- 3.4.2.1 Singleton Fuzzifier -- 3.4.2.2 Non-Singleton Fuzzifier -- 3.5 Combining Fired-Rule Output Sets on the Way to Defuzzification -- 3.5.1 Mamdani Fuzzy System: Combining Using Set Theoretic Operations -- 3.5.2 Mamdani Fuzzy System: Combining Using a Weighted Combination -- 3.5.3 Mamdani and TSK Fuzzy Systems: Combining During Defuzzification -- 3.6 Defuzzifier -- 3.6.1 Mamdani Fuzzy System: Centroid Defuzzifier -- 3.6.2 Mamdani Fuzzy System: Height Defuzzifier -- 3.6.3 Mamdani Fuzzy System: COS Defuzzifier -- 3.6.4 TSK Fuzzy System Defuzzifiers -- 3.7 Comprehensive Example -- 3.8 Fuzzy Basis Functions -- 3.9 Sculpting the State Space and the Potential for Improved Performance over a Non-Fuzzy System -- 3.9.1 Course Sculpting of the State Space -- 3.9.2 Fine Sculpting of the State Space -- 3.9.3 Observations -- 3.10 Remarks and Insights -- 3.10.1 Unique Features of Type-1 Fuzzy Systems -- 3.10.2 Layered Architecture Interpretations of a Fuzzy System -- 3.10.3 Functional Equivalence to Other Machine Learning Methods -- 3.10.4 Universal Approximation by Fuzzy Systems -- 3.10.5 Continuity of Fuzzy Systems -- 3.10.6 Rule Explosion and Some Ways to Control It -- 3.10.7 Interpretable and Explainable T1 Fuzzy Systems -- 3.10.7.1 Introduction. 3.10.7.2 On Interpretable -- 3.10.7.3 On Explainable -- 3.10.8 A Top-Down Approach to T1 Fuzzy Systems -- 1.1 Evaluation of Sup-Star Composition for Minimum t-Norm -- 1.2 Evaluation of Sup-Star Composition for Product t-Norm -- 1.3 A Novel Suggestion -- Appendix 2: Constructing Type-1 Rule Partitions -- 2.1 Singleton Fuzzification: T1 First-Order Rule Partitions -- 2.2 Singleton Fuzzification: T1 Second-Order Rule Partitions -- 2.3 Non-Singleton Fuzzification: T1 First-Order Rule Partitions -- 2.4 Non-Singleton Fuzzification: T1 Second-Order Rule Partitions -- 2.5 Rule Crossover Phenomenon -- Appendix 3: Procedure for Determining the Active Rules in a First-Order Rule Partition -- 3.1 First-Order Rule Partition Information Table -- 3.2 Indexing Rules -- 3.3 Determining Rules Associated with x = x′ -- References -- 4: Type-1 Fuzzy Systems: Design Methods and Case Studies -- 4.1 Designing Type-1 Fuzzy Systems -- 4.1.1 Design Choices and Complexity -- 4.1.2 An Interpretation for the Design of a Type-1 Fuzzy System -- 4.1.3 Recapitulation of Mamdani and TSK Fuzzy Systems -- 4.1.4 Number of Design Degrees of Freedom and a Design Principle -- 4.1.5 High-Level Design Statements and Design Approaches -- 4.2 Some Design Methods -- 4.2.1 One-Pass Methods -- 4.2.1.1 Data Assignment Method -- 4.2.1.2 WM Method -- 4.2.2 Clustering Using Fuzzy c-Means (FCM) -- 4.2.3 Least Squares (LS) Method -- 4.2.4 Derivative-Based Methods (Back-Propagation) -- 4.2.5 Derivative-Free Methods -- 4.2.6 Hybrid Design Methods -- 4.2.6.1 Adaptive Network Fuzzy Inference System (ANFIS) -- 4.2.6.2 Structure Identification and Feature Extraction (SIFE) for TSK Systems -- 4.2.7 Remarks -- 4.3 Case Study: Forecasting of Time-Series -- 4.3.1 Mackey-Glass Chaotic Time Series -- 4.3.2 One-Pass Design: Singleton Fuzzification -- 4.3.3 Derivative-Based (BP) Design: Singleton Fuzzification. 4.3.4 A Change in the Measurements -- 4.3.5 One-Pass Design: Non-singleton Fuzzification -- 4.3.6 Derivative-Based (BP) Design: Non-singleton Fuzzification -- 4.3.7 Final Remark -- 4.4 Case Study: Knowledge Mining Using Surveys -- 4.4.1 Methodology for Knowledge Mining -- 4.4.2 Survey Results -- 4.4.3 Determining Type-1 Fuzzy Sets from Survey Results -- 4.4.4 What Does One Do with a Histogram of Responses? -- 4.4.5 Averaging the Responses: Consensus FLAs -- 4.4.6 Preserving All of the Responses -- 4.4.7 On Multiple Indicators -- 4.4.8 How to Use an FLA -- 4.4.9 Connections to the Perceptual Computer -- 4.5 Case Study: Rule-Based Classification of Video Traffic -- 4.5.1 Compressed Video Traffic -- 4.5.2 High-Level Video Classification Problem -- 4.5.3 Selected Features -- 4.5.4 MFs for the Features -- 4.5.5 Rules and Their Parameters -- 4.5.6 Computational Formulas for the RBC -- 4.5.7 Optimization of Rule Design Parameters -- 4.5.8 Testing the FL RBC -- 4.5.9 Results and Conclusions -- 4.6 Case Study: Fuzzy Logic Control -- 4.6.1 Early History of Fuzzy Control -- 4.6.2 What Is a Type-1 Fuzzy Logic Controller (FLC)? -- 4.6.3 Fuzzy PID Control -- 4.6.3.1 Background -- 4.6.3.2 General Structure of Fuzzy PID Controller -- 4.6.3.3 Conventional and Fuzzy PID Controller Design Methods -- 4.6.3.4 Simulation Results (T1-FPID Versus PID) -- 4.7 Case Study: Explainable Type-1 Fuzzy System -- 4.7.1 Computations Common to Both Fuzzy Systems -- 4.7.1.1 Firing Levels for the Active Rules -- 4.7.1.2 Similarities -- 4.7.2 Mamdani with Centroid Defuzzification -- 4.7.2.1 Computation of yc (2.4, 5.4, 9) -- 4.7.2.2 Explaining yc (2.4,5.4,9) -- 4.7.2.3 Quality of Explanation -- 4.7.3 Mamdani with COS Defuzzification -- 4.7.3.1 Computation of yCOS(2.4,5.4,9) -- 4.7.3.2 Explaining yCOS(2.4,5.4,9) -- 4.7.3.3 Observations -- 1.1 Count of MF Parameters. 1.2 T1 MF Constraints -- 1.3 Determine If Satisfying All of the Constraints Is Possible -- 1.4 Constraints Almost Always-Satisfied Parameters (CAASPs) -- 1.5 Comments -- 1.6 Optimizing T1 MF Parameters -- References -- 5: Sources of Uncertainty and Membership Functions -- 5.1 Uncertainties in a Fuzzy System -- 5.1.1 Uncertainty: General Discussions -- 5.1.2 Uncertainties and Sets -- 5.1.3 Uncertainties in a Fuzzy System -- 5.2 Words Mean Different Things to Different People -- 5.2.1 Collecting Word Data by Means of a Survey -- 5.2.2 Making Use of Word Uncertainties -- 5.2.3 Conclusion -- 5.3 Words Must Also Mean Similar Things to Different People -- 5.3.1 Probability-Based Solution of (5.1) -- 5.3.2 Iterative Solution of (5.1)s -- 5.3.3 Example -- 5.4 From Interval Data to a T1 FS -- 5.4.1 Mean and Standard Deviation for Each Data Interval -- 5.4.2 T1 FS Models and Their Mean and Standard Deviation -- 5.4.3 Computation of MF Parameters -- 5.4.4 Choice of T1 MF -- 5.4.5 Ensemble of T1 MFs -- References -- 6: Type-2 Fuzzy Sets Including Word Models -- 6.1 The Concept of a Type-2 Fuzzy Set -- 6.2 Definitions of a General Type-2 Fuzzy Set and Associated Concepts -- 6.3 Definitions of an IT2 FS and Associated Concepts -- 6.4 Examples of Two Popular FOUs -- 6.5 Interval Type-2 Fuzzy Numbers -- 6.6 Different Kinds of T2 FSs: Hierarchy -- 6.7 Mathematical Representations for T2 FSs -- 6.7.1 Vertical Slice Representation -- 6.7.2 Wavy Slice Representations -- 6.7.2.1 General Case -- 6.7.2.2 Covering the FOU -- 6.7.2.3 Minimal Coverings -- 6.7.2.4 Comments -- 6.7.3 Horizontal Slice Representation -- 6.7.4 Modeling Secondary MFs -- 6.8 Representing Non-T2 FSs as T2 FSs -- 6.9 Returning to Linguistic Labels for General T2 FSs -- 6.10 Multivariable Membership Functions -- 6.11 IT2 FS Word Models -- References -- 7: Working with Type-2 Fuzzy Sets. 7.1 Introduction and Guide for the Reader. |
| Record Nr. | UNINA-9910831020703321 |
|
Mendel Jerry M
|
||
| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fault-Tolerant Control for Time-Varying Delayed T-S Fuzzy Systems [[electronic resource] /] / by Shaoxin Sun, Huaguang Zhang, Xiaojie Su, Jinyu Zhu
| Fault-Tolerant Control for Time-Varying Delayed T-S Fuzzy Systems [[electronic resource] /] / by Shaoxin Sun, Huaguang Zhang, Xiaojie Su, Jinyu Zhu |
| Autore | Sun Shaoxin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (230 pages) |
| Disciplina | 511.313 |
| Altri autori (Persone) |
ZhangHuaguang
SuXiaojie ZhuJinyu |
| Collana | Intelligent Control and Learning Systems |
| Soggetto topico |
Control engineering
System theory Control theory Stochastic processes Automation Control and Systems Theory Systems Theory, Control Stochastic Systems and Control |
| Soggetto non controllato |
System Theory
Robotics Automation Science Technology & Engineering |
| ISBN |
9789819913572
9789819913565 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1 Introduction -- Chapter 2 Fault Estimation and Tolerant Control for Time-Varying Delayed Fuzzy Systems with Actuator Faults -- Chapter 3 Fault Estimation and Tolerant Control for Multiple Time Delayed Fuzzy Systems with Sensor and Actuator Faults -- Chapter 4 Multiple Intermittent Fault Estimation and Tolerant Control for Switched T-S Fuzzy Stochastic Systems with Multiple Delays -- Chapter 5 Fault-Tolerant Control for Multiple Interval Time Delayed Switched Fuzzy Systems With Intermittent Faults -- Chapter 6 Fault-Tolerant Control for Multiple-Delayed Switched Fuzzy Stochastic Systems With Intermittent Faults -- Chapter 7 Conclusion and Prospect. |
| Record Nr. | UNINA-9910725098903321 |
|
Sun Shaoxin
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics : Theory and Applications
| A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics : Theory and Applications |
| Autore | de Barros Laécio Carvalho |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (324 pages) |
| Disciplina | 511.313 |
| Altri autori (Persone) |
BassaneziRodney Carlos
LodwickWeldon A |
| Collana | Studies in Fuzziness and Soft Computing Series |
| ISBN | 3-031-50492-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910845487703321 |
|
de Barros Laécio Carvalho
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics [[electronic resource] ] : Theory and Applications / / by Laécio Carvalho de Barros, Rodney Carlos Bassanezi, Weldon Alexander Lodwick
| A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics [[electronic resource] ] : Theory and Applications / / by Laécio Carvalho de Barros, Rodney Carlos Bassanezi, Weldon Alexander Lodwick |
| Autore | de Barros Laécio Carvalho |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVI, 299 p. 113 illus., 15 illus. in color.) |
| Disciplina | 511.313 |
| Collana | Studies in Fuzziness and Soft Computing |
| Soggetto topico |
Computational intelligence
Biomathematics Statistics Computational Intelligence Mathematical and Computational Biology Statistics for Life Sciences, Medicine, Health Sciences |
| ISBN | 3-662-53324-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Fuzzy Sets Theory and Uncertainty in Mathematical Modeling -- The Extension Principle of Zadeh and Fuzzy Numbers -- Fuzzy Relations -- Notions of Fuzzy Logic -- Fuzzy Rule-Based Systems. |
| Record Nr. | UNINA-9910254353503321 |
|
de Barros Laécio Carvalho
|
||
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fuzzy approaches for soft computing and approximate reasoning : theories and applications : dedicated to Bernadette Bouchon-Meunier / / Marie-Jeanne Lesot, Christophe Marsala, editors
| Fuzzy approaches for soft computing and approximate reasoning : theories and applications : dedicated to Bernadette Bouchon-Meunier / / Marie-Jeanne Lesot, Christophe Marsala, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XX, 297 p. 49 illus., 32 illus. in color.) |
| Disciplina | 511.313 |
| Collana | Studies in fuzziness and soft computing |
| Soggetto topico | Fuzzy systems |
| ISBN | 3-030-54341-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: The Fuzzy Theoretic Turn -- Chapter 2: Membership functions -- Chapter 3: The evolution of the notion of overlap functions -- Chapter 4: Interpolative reasoning: valid, specificity-gradual -- Chapter 5: A similarity-based three-valued modal logic approach to reason with prototypes and counterexamples -- Chapter 6: Analogy -- Chapter 7: The role of the context in decision and optimization problems -- Chapter 8: Decision rules under vague and uncertain information -- Chapter 9: Abstract Models for Systems Identification -- Chapter 10: Fuzzy Systems Interpretability: What, Why and How -- Chapter 11: Fuzzy Clustering Models and Their Related Concepts. |
| Record Nr. | UNINA-9910483053103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fuzzy computing in data science : applications and challenges / / edited by Sachi Nandan Mohanty, Prasenjit Chatterjee and Bui Thanh Hung
| Fuzzy computing in data science : applications and challenges / / edited by Sachi Nandan Mohanty, Prasenjit Chatterjee and Bui Thanh Hung |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] |
| Descrizione fisica | 1 online resource (363 pages) |
| Disciplina | 511.313 |
| Collana | Smart and sustainable intelligent systems |
| Soggetto topico |
Fuzzy logic
Fuzzy systems Data mining |
| ISBN |
1-394-15688-X
1-394-15687-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Dedication Page -- Contents -- Preface -- Acknowledgement -- Chapter 1 Band Reduction of HSI Segmentation Using FCM -- 1.1 Introduction -- 1.2 Existing Method -- 1.2.1 K-Means Clustering Method -- 1.2.2 Fuzzy C-Means -- 1.2.3 Davies Bouldin Index -- 1.2.4 Data Set Description of HSI -- 1.3 Proposed Method -- 1.3.1 Hyperspectral Image Segmentation Using Enhanced Estimation of Centroid -- 1.3.2 Band Reduction Using K-Means Algorithm -- 1.3.3 Band Reduction Using Fuzzy C-Means -- 1.4 Experimental Results -- 1.4.1 DB Index Graph -- 1.4.2 K-Means-Based PSC (EEOC) -- 1.4.3 Fuzzy C-Means-Based PSC (EEOC) -- 1.5 Analysis of Results -- 1.6 Conclusions -- References -- Chapter 2 A Fuzzy Approach to Face Mask Detection -- 2.1 Introduction -- 2.2 Existing Work -- 2.3 The Proposed Framework -- 2.4 Set-Up and Libraries Used -- 2.5 Implementation -- 2.6 Results and Analysis -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Application of Fuzzy Logic to the Healthcare Industry -- 3.1 Introduction -- 3.2 Background -- 3.3 Fuzzy Logic -- 3.4 Fuzzy Logic in Healthcare -- 3.5 Conclusions -- References -- Chapter 4 A Bibliometric Approach and Systematic Exploration of Global Research Activity on Fuzzy Logic in Scopus Database -- 4.1 Introduction -- 4.2 Data Extraction and Interpretation -- 4.3 Results and Discussion -- 4.3.1 Per Year Publication and Citation Count -- 4.3.2 Prominent Affiliations Contributing Toward Fuzzy Logic -- 4.3.3 Top Journals Emerging in Fuzzy Logic in Major Subject Areas -- 4.3.4 Major Contributing Countries Toward Fuzzy Research Articles -- 4.3.5 Prominent Authors Contribution Toward the Fuzzy Logic Analysis -- 4.3.6 Coauthorship of Authors -- 4.3.7 Cocitation Analysis of Cited Authors -- 4.3.8 Cooccurrence of Author Keywords.
4.4 Bibliographic Coupling of Documents, Sources, Authors, and Countries -- 4.4.1 Bibliographic Coupling of Documents -- 4.4.2 Bibliographic Coupling of Sources -- 4.4.3 Bibliographic Coupling of Authors -- 4.4.4 Bibliographic Coupling of Countries -- 4.5 Conclusion -- References -- Chapter 5 Fuzzy Decision Making in Predictive Analytics and Resource Scheduling -- 5.1 Introduction -- 5.2 History of Fuzzy Logic and Its Applications -- 5.3 Approximate Reasoning -- 5.4 Fuzzy Sets vs Classical Sets -- 5.5 Fuzzy Inference System -- 5.5.1 Characteristics of FIS -- 5.5.2 Working of FIS -- 5.5.3 Methods of FIS -- 5.6 Fuzzy Decision Trees -- 5.6.1 Characteristics of Decision Trees -- 5.6.2 Construction of Fuzzy Decision Trees -- 5.7 Fuzzy Logic as Applied to Resource Scheduling in a Cloud Environment -- 5.8 Conclusion -- References -- Chapter 6 Application of Fuzzy Logic and Machine Learning Concept in Sales Data Forecasting Decision Analytics Using ARIMA Model -- 6.1 Introduction -- 6.1.1 Aim and Scope -- 6.1.2 R-Tool -- 6.1.3 Application of Fuzzy Logic -- 6.1.4 Dataset -- 6.2 Model Study -- 6.2.1 Introduction to Machine Learning Method -- 6.2.2 Time Series Analysis -- 6.2.3 Components of a Time Series -- 6.2.4 Concepts of Stationary -- 6.2.5 Model Parsimony -- 6.3 Methodology -- 6.3.1 Exploratory Data Analysis -- 6.3.1.1 Seed Types-Analysis -- 6.3.1.2 Comparison of Location and Seeds -- 6.3.1.3 Comparison of Season (Month) and Seeds -- 6.3.2 Forecasting -- 6.3.2.1 Auto Regressive Integrated Moving Average (ARIMA) -- 6.3.2.2 Data Visualization -- 6.3.2.3 Implementation Model -- 6.4 Result Analysis -- 6.5 Conclusion -- References -- Chapter 7 Modified m-Polar Fuzzy Set ELECTRE-I Approach -- 7.1 Introduction -- 7.1.1 Objectives -- 7.2 Implementation of m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculations. 7.2.1 The m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculation Method -- 7.3 Application to Industrial Problems -- 7.3.1 Cutting Fluid Selection Problem -- 7.3.2 Results Obtained From m-Polar Fuzzy ELECTRE-I for Cutting Fluid Selection Problem -- 7.3.3 FMS Selection Problem -- 7.3.4 Results Obtained From m-Polar Fuzzy ELECTRE-I for FMS Selection -- 7.4 Conclusions -- References -- Chapter 8 Fuzzy Decision Making: Concept and Models -- 8.1 Introduction -- 8.2 Classical Set -- 8.3 Fuzzy Set -- 8.4 Properties of Fuzzy Set -- 8.5 Types of Decision Making -- 8.5.1 Individual Decision Making -- 8.5.2 Multiperson Decision Making -- 8.5.3 Multistage Decision Making -- 8.5.4 Multicriteria Decision Making -- 8.6 Methods of Multiattribute Decision Making (MADM) -- 8.6.1 Weighted Sum Method (WSM) -- 8.6.2 Weighted Product Method (WPM) -- 8.6.3 Weighted Aggregates Sum Product Assessment (WASPAS) -- 8.6.4 Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) -- 8.7 Applications of Fuzzy Logic -- 8.8 Conclusion -- References -- Chapter 9 Use of Fuzzy Logic for Psychological Support to Migrant Workers of Southern Odisha (India) -- 9.1 Introduction -- 9.2 Objectives and Methodology -- 9.2.1 Objectives -- 9.2.2 Methodology -- 9.3 Effect of COVID-19 on the Psychology and Emotion of Repatriated Migrants -- 9.3.1 Psychological Variables Identified -- 9.3.2 Fuzzy Logic for Solace to Migrants -- 9.4 Findings -- 9.5 Way Out for Strengthening the Psychological Strength of the Migrant Workers through Technological Aid -- 9.6 Conclusion -- References -- Chapter 10 Fuzzy-Based Edge AI Approach: Smart Transformation of Healthcare for a Better Tomorrow -- 10.1 Significance of Machine Learning in Healthcare -- 10.2 Cloud-Based Artificial Intelligent Secure Models -- 10.3 Applications and Usage of Machine Learning in Healthcare. 10.3.1 Detecting Diseases and Diagnosis -- 10.3.2 Drug Detection and Manufacturing -- 10.3.3 Medical Imaging Analysis and Diagnosis -- 10.3.4 Personalized/Adapted Medicine -- 10.3.5 Behavioral Modification -- 10.3.6 Maintenance of Smart Health Data -- 10.3.7 Clinical Trial and Study -- 10.3.8 Crowdsourced Information Discovery -- 10.3.9 Enhanced Radiotherapy -- 10.3.10 Outbreak/Epidemic Prediction -- 10.4 Edge AI: For Smart Transformation of Healthcare -- 10.4.1 Role of Edge in Reshaping Healthcare -- 10.4.2 How AI Powers the Edge -- 10.5 Edge AI-Modernizing Human Machine Interface -- 10.5.1 Rural Medicine -- 10.5.2 Autonomous Monitoring of Hospital Rooms-A Case Study -- 10.6 Significance of Fuzzy in Healthcare -- 10.6.1 Fuzzy Logic-Outline -- 10.6.2 Fuzzy Logic-Based Smart Healthcare -- 10.6.3 Medical Diagnosis Using Fuzzy Logic for Decision Support Systems -- 10.6.4 Applications of Fuzzy Logic in Healthcare -- 10.7 Conclusion and Discussions -- References -- Chapter 11 Video Conferencing (VC) Software Selection Using Fuzzy TOPSIS -- 11.1 Introduction -- 11.2 Video Conferencing Software and Its Major Features -- 11.2.1 Video Conferencing/Meeting Software (VC/MS) for Higher Education Institutes -- 11.3 Fuzzy TOPSIS -- 11.3.1 Extension of TOPSIS Algorithm: Fuzzy TOPSIS -- 11.4 Sample Numerical Illustration -- 11.5 Conclusions -- References -- Chapter 12 Estimation of Nonperforming Assets of Indian Commercial Banks Using Fuzzy AHP and Goal Programming -- 12.1 Introduction -- 12.1.1 Basic Concepts of Fuzzy AHP and Goal Programming -- 12.2 Research Model -- 12.2.1 Average Growth Rate Calculation -- 12.3 Result and Discussion -- 12.4 Conclusion -- References -- Chapter 13 Evaluation of Ergonomic Design for the Visual Display Terminal Operator at Static Work Under FMCDM Environment -- 13.1 Introduction -- 13.2 Proposed Algorithm. 13.3 An Illustrative Example on Ergonomic Design Evaluation -- 13.4 Conclusions -- References -- Chapter 14 Optimization of Energy Generated from Ocean Wave Energy Using Fuzzy Logic -- 14.1 Introduction -- 14.2 Control Approach in Wave Energy Systems -- 14.3 Related Work -- 14.4 Mathematical Modeling for Energy Conversion from Ocean Waves -- 14.5 Proposed Methodology -- 14.5.1 Wave Parameters -- 14.5.2 Fuzzy-Optimizer -- 14.6 Conclusion -- References -- Chapter 15 The m-Polar Fuzzy TOPSIS Method for NTM Selection -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Methodology -- 15.3.1 Steps of the mFS TOPSIS -- 15.4 Case Study -- 15.4.1 Effect of Analytical Hierarchy Process (AHP) Weight Calculation on the mFS TOPSIS Method -- 15.4.2 Effect of Shannon's Entropy Weight Calculation on the m-Polar Fuzzy Set TOPSIS Method -- 15.5 Results and Discussions -- 15.5.1 Result Validation -- 15.6 Conclusions and Future Scope -- References -- Chapter 16 Comparative Analysis on Material Handling Device Selection Using Hybrid FMCDM Methodology -- 16.1 Introduction -- 16.2 MCDM Techniques -- 16.2.1 FAHP -- 16.2.2 Entropy Method as Weights (Influence) Evaluation Technique -- 16.3 The Proposed Hybrid and Super Hybrid FMCDM Approaches -- 16.3.1 TOPSIS -- 16.3.2 FMOORA Method -- 16.3.3 FVIKOR -- 16.3.4 Fuzzy Grey Theory (FGT) -- 16.3.5 COPRAS -G -- 16.3.6 Super Hybrid Algorithm -- 16.4 Illustrative Example -- 16.5 Results and Discussions -- 16.5.1 FTOPSIS -- 16.5.2 FMOORA -- 16.5.3 FVIKOR -- 16.5.4 Fuzzy Grey Theory (FGT) -- 16.5.5 COPRAS-G -- 16.5.6 Super Hybrid Approach (SHA) -- 16.6 Conclusions -- References -- Chapter 17 Fuzzy MCDM on CCPM for Decision Making: A Case Study -- 17.1 Introduction -- 17.2 Literature Review -- 17.3 Objective of Research -- 17.4 Cluster Analysis -- 17.4.1 Hierarchical Clustering -- 17.4.2 Partitional Clustering -- 17.5 Clustering. 17.6 Methodology. |
| Record Nr. | UNINA-9910830507603321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
